Nipah Virus Using Restricted Boltzmann Machine

Abstract

Nipah virus is an infectious virus which is caused by fruit bats. Recently in 2018, there was a deadly outbreak that occurred in Kerala where many of people got infected and died due to Nipah virus. In this model, we are using deep learning concept which helps to predict the occurrence of infected virus using restricted Boltzmann machine. It is a feature selection algorithm where particular data will be selected by applying matrix of weights associated with the connection between the hidden layer and the visible layer. Firstly, it was identified in Malaysia Kampung Sungai Nipah in 1998. The fertility rate people affected with Nipah virus was around 70%. Transmission of this infected virus is done by bats-to-human, animals-to-human and human-to-human. Particular signs and symptoms will be exhibited for the person affected with Nipah virus. Cerebrospinal fluid serum test will be done by collecting white blood cells, glucose and protein by using restricted Boltzmann machine. This deep learning algorithm will give the numeric results such that we can identify whether the patient is affected with Nipah virus. Prevention measures should be taken as “prevention is better than cure” because there is no vaccine for Nipah virus which is eventually more dangerous.